Untitled
coop711
2017 10 6
Packages and Data
library(GISTools)## Loading required package: maptools## Loading required package: sp## Checking rgeos availability: TRUE## Loading required package: RColorBrewer## Loading required package: MASS## Loading required package: rgeos## rgeos version: 0.3-25, (SVN revision 555)
## GEOS runtime version: 3.6.1-CAPI-1.10.1 r0
## Linking to sp version: 1.2-5
## Polygon checking: TRUElibrary(tidyverse)## Loading tidyverse: ggplot2
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr## Conflicts with tidy packages ----------------------------------------------## filter(): dplyr, stats
## lag(): dplyr, stats
## select(): dplyr, MASSlibrary(broom)
library(rgeos)
data(georgia)
ls()## [1] "georgia" "georgia.polys" "georgia2"Georgia Maps
plot(georgia)
plot(georgia,
col = "red",
bg = "wheat")
class(georgia)## [1] "SpatialPolygonsDataFrame"
## attr(,"package")
## [1] "sp"georgia_outline <- gUnaryUnion(georgia,
id = NULL)
plot(georgia,
asp = 1,
col = "red",
bg = "wheat",
lty = 2,
border = "blue")
plot(georgia_outline,
asp = 1,
lwd = 3,
add = TRUE)
title(main = "The State of Georgia",
font.main = 2,
cex.main = 1.5,
sub = "and its counties",
font.sub = 3,
col.sub = "blue")
par(mfrow = c(1, 2),
mar = c(2, 0, 3, 0))
plot(georgia,
col = "red",
bg = "wheat")
title("georgia")
plot(georgia2,
col = "orange",
bg = "lightyellow")
title("georgia2")
par(mfrow = c(1,1))georgia
str(georgia@data)## 'data.frame': 159 obs. of 14 variables:
## $ Latitude: num 31.8 31.3 31.6 31.3 33.1 ...
## $ Longitud: num -82.3 -82.9 -82.5 -84.5 -83.3 ...
## $ TotPop90: num 15744 6213 9566 3615 39530 ...
## $ PctRural: num 75.6 100 61.7 100 42.7 100 64.6 75.2 47 66.2 ...
## $ PctBach : num 8.2 6.4 6.6 9.4 13.3 6.4 9.2 9 7.6 7.5 ...
## $ PctEld : num 11.43 11.77 11.11 13.17 8.64 ...
## $ PctFB : num 0.64 1.58 0.27 0.11 1.43 0.34 0.92 0.82 0.33 1.19 ...
## $ PctPov : num 19.9 26 24.1 24.8 17.5 15.1 14.7 10.7 22 19.3 ...
## $ PctBlack: num 20.8 26.9 15.4 51.7 42.4 ...
## $ X : num 941397 895553 930946 745399 849431 ...
## $ Y : num 3521764 3471916 3502787 3474765 3665553 ...
## $ ID : int 13001 13003 13005 13007 13009 13011 13013 13015 13017 13019 ...
## $ Name : chr "Appling" "Atkinson" "Bacon" "Baker" ...
## $ MedInc : num 32152 27657 29342 29610 36414 ...georgia$Name## [1] "Appling" "Atkinson" "Bacon" "Baker"
## [5] "Baldwin" "Banks" "Barrow" "Bartow"
## [9] "Ben Hill" "Berrien" "Bibb" "Bleckley"
## [13] "Brantley" "Brooks" "Bryan" "Bulloch"
## [17] "Burke" "Butts" "Calhoun" "Camden"
## [21] "Candler" "Carroll" "Catoosa" "Charlton"
## [25] "Chatham" "Chattahoochee" "Chattooga" "Cherokee"
## [29] "Clarke" "Clay" "Clayton" "Clinch"
## [33] "Cobb" "Coffee" "Colquitt" "Columbia"
## [37] "Cook" "Coweta" "Crawford" "Crisp"
## [41] "Dade" "Dawson" "Decatur" "DeKalb"
## [45] "Dodge" "Dooly" "Dougherty" "Douglas"
## [49] "Early" "Echols" "Effingham" "Elbert"
## [53] "Emanuel" "Evans" "Fannin" "Fayette"
## [57] "Floyd" "Forsyth" "Franklin" "Fulton"
## [61] "Gilmer" "Glascock" "Glynn" "Gordon"
## [65] "Grady" "Greene" "Gwinnett" "Habersham"
## [69] "Hall" "Hancock" "Haralson" "Harris"
## [73] "Hart" "Heard" "Henry" "Houston"
## [77] "Irwin" "Jackson" "Jasper" "Jeff Davis"
## [81] "Jefferson" "Jenkins" "Johnson" "Jones"
## [85] "Lamar" "Lanier" "Laurens" "Lee"
## [89] "Liberty" "Lincoln" "Long" "Lowndes"
## [93] "Lumpkin" "McDuffie" "McIntosh" "Macon"
## [97] "Madison" "Marion" "Meriwether" "Miller"
## [101] "Mitchell" "Monroe" "Montgomery" "Morgan"
## [105] "Murray" "Muscogee" "Newton" "Oconee"
## [109] "Oglethorpe" "Paulding" "Peach" "Pickens"
## [113] "Pierce" "Pike" "Polk" "Pulaski"
## [117] "Putnam" "Quitman" "Rabun" "Randolph"
## [121] "Richmond" "Rockdale" "Schley" "Screven"
## [125] "Seminole" "Spalding" "Stephens" "Stewart"
## [129] "Sumter" "Talbot" "Taliaferro" "Tattnall"
## [133] "Taylor" "Telfair" "Terrell" "Thomas"
## [137] "Tift" "Toombs" "Towns" "Treutlen"
## [141] "Troup" "Turner" "Twiggs" "Union"
## [145] "Upson" "Walker" "Walton" "Ware"
## [149] "Warren" "Washington" "Wayne" "Webster"
## [153] "Wheeler" "White" "Whitfield" "Wilcox"
## [157] "Wilkes" "Wilkinson" "Worth"georgia$id <- as.character(0:(nrow(georgia@data) - 1))
georgia_df <- georgia %>%
tidy()## Regions defined for each Polygonsstr(georgia_df)## 'data.frame': 14909 obs. of 7 variables:
## $ long : num -82.2 -82.2 -82.2 -82.2 -82.2 ...
## $ lat : num 31.9 31.9 31.9 31.9 31.9 ...
## $ order: int 1 2 3 4 5 6 7 8 9 10 ...
## $ hole : logi FALSE FALSE FALSE FALSE FALSE FALSE ...
## $ piece: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
## $ group: Factor w/ 162 levels "0.1","1.1","2.1",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ id : chr "0" "0" "0" "0" ...table(sort(georgia_df$id))##
## 0 1 10 100 101 102 103 104 105 106 107 108 109 11 110 111 112 113
## 125 99 107 96 51 93 85 138 105 100 111 128 25 26 62 40 187 64
## 114 115 116 117 118 119 12 120 121 122 123 124 125 126 127 128 129 13
## 24 48 92 54 163 64 163 115 57 35 218 82 86 47 83 86 107 157
## 130 131 132 133 134 135 136 137 138 139 14 140 141 142 143 144 145 146
## 99 114 147 208 73 34 47 91 65 91 287 32 57 136 128 87 27 67
## 147 148 149 15 150 151 152 153 154 155 156 157 158 16 17 18 19 2
## 94 123 189 190 171 48 165 113 121 116 137 121 102 136 77 93 227 53
## 20 21 22 23 24 25 26 27 28 29 3 30 31 32 33 34 35 36
## 37 56 30 256 180 96 32 47 68 68 124 73 64 59 92 67 87 115
## 37 38 39 4 40 41 42 43 44 45 46 47 48 49 5 50 51 52
## 108 117 43 116 14 56 50 54 91 67 48 44 89 58 57 205 125 133
## 53 54 55 56 57 58 59 6 60 61 62 63 64 65 66 67 68 69
## 56 73 111 71 72 54 150 88 97 64 138 75 25 105 74 125 95 125
## 7 70 71 72 73 74 75 76 77 78 79 8 80 81 82 83 84 85
## 48 17 73 57 22 119 155 60 94 72 97 69 109 26 58 42 17 54
## 86 87 88 89 9 90 91 92 93 94 95 96 97 98 99
## 72 76 221 99 160 150 176 106 117 143 81 126 74 82 24georgia_df <- left_join(georgia@data, georgia_df,
by = c("id" = "id"))
str(georgia_df)## 'data.frame': 14909 obs. of 21 variables:
## $ Latitude: num 31.8 31.8 31.8 31.8 31.8 ...
## $ Longitud: num -82.3 -82.3 -82.3 -82.3 -82.3 ...
## $ TotPop90: num 15744 15744 15744 15744 15744 ...
## $ PctRural: num 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 75.6 ...
## $ PctBach : num 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 8.2 ...
## $ PctEld : num 11.4 11.4 11.4 11.4 11.4 ...
## $ PctFB : num 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 0.64 ...
## $ PctPov : num 19.9 19.9 19.9 19.9 19.9 19.9 19.9 19.9 19.9 19.9 ...
## $ PctBlack: num 20.8 20.8 20.8 20.8 20.8 ...
## $ X : num 941397 941397 941397 941397 941397 ...
## $ Y : num 3521764 3521764 3521764 3521764 3521764 ...
## $ ID : int 13001 13001 13001 13001 13001 13001 13001 13001 13001 13001 ...
## $ Name : chr "Appling" "Appling" "Appling" "Appling" ...
## $ MedInc : num 32152 32152 32152 32152 32152 ...
## $ id : chr "0" "0" "0" "0" ...
## $ long : num -82.2 -82.2 -82.2 -82.2 -82.2 ...
## $ lat : num 31.9 31.9 31.9 31.9 31.9 ...
## $ order : int 1 2 3 4 5 6 7 8 9 10 ...
## $ hole : logi FALSE FALSE FALSE FALSE FALSE FALSE ...
## $ piece : Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
## $ group : Factor w/ 162 levels "0.1","1.1","2.1",..: 1 1 1 1 1 1 1 1 1 1 ...ggplot(georgia_df, aes(x = long, y = lat, group = group)) +
geom_polygon(fill = "white", colour = "black") +
geom_text(aes(x = Longitud, y = Latitude, label = Name), size = 1) +
coord_map()
County Names
Lat <- data.frame(georgia)[, 1] #> georgia$Latitude
Lon <- data.frame(georgia)[, 2] #> georgia$Longitud
Names <- data.frame(georgia)[, 13] #> georgia$Name
plot(georgia,
col = NA)
text(Lon, Lat,
labels = Names,
cex = 0.5) #> Better than `pointLabel`
# pl <- pointLabel(Lon, Lat, Names, offset = 0, cex = 0.5)Subregion
counties <- c("Jefferson", "Jenkins", "Johnson", "Washington", "Glascock", "Emanuel", "Candler", "Bulloch", "Screven", "Richmond", "Burke")
counties_idx <- which(georgia$Name %in% counties)
counties_idx## [1] 16 17 21 53 62 81 82 83 121 124 150georgia_sub <- georgia[counties_idx, ]
plot(georgia_sub,
col = "gold1",
border = "grey")
plot(georgia_outline,
add = TRUE,
lwd = 2)
text(Lon[counties_idx], Lat[counties_idx],
labels = Names[counties_idx],
cex = 1)
plot(georgia,
border = "grey",
lwd = 0.5)
plot(georgia_sub,
col = "lightblue",
add = TRUE)
plot(georgia_outline,
lwd = 2,
add = TRUE)
title("Georgia with a subset of counties")
Open Street Map
# install.packages("OpenStreetMap", dependencies = TRUE)
library(OpenStreetMap)
ul <- as.vector(cbind(bbox(georgia_sub)[2, 2],
bbox(georgia_sub)[1, 1]))
lr <- as.vector(cbind(bbox(georgia_sub)[2, 1],
bbox(georgia_sub)[1, 2]))
MyMap <- openmap(upperLeft = ul,
lowerRight = lr,
zoom = 9,
type = 'osm') #> Try various `maptype`
plot(MyMap, removeMargin = FALSE)
plot(spTransform(georgia_sub,
osm()),
lwd = 2,
add = TRUE)
RgoogleMaps, PBSmapping
# install.packages(c("RgoogleMaps", "PBSmapping"))
library(RgoogleMaps)
library(PBSmapping)##
## -----------------------------------------------------------
## PBS Mapping 2.70.4 -- Copyright (C) 2003-2017 Fisheries and Oceans Canada
##
## PBS Mapping comes with ABSOLUTELY NO WARRANTY;
## for details see the file COPYING.
## This is free software, and you are welcome to redistribute
## it under certain conditions, as outlined in the above file.
##
## A complete user guide 'PBSmapping-UG.pdf' is located at
## /Library/Frameworks/R.framework/Versions/3.4/Resources/library/PBSmapping/doc/PBSmapping-UG.pdf
##
## Packaged on 2017-06-28
## Pacific Biological Station, Nanaimo
##
## All available PBS packages can be found at
## https://github.com/pbs-software
##
## To see demos, type '.PBSfigs()'.
## -----------------------------------------------------------shp <- SpatialPolygons2PolySet(georgia_sub)
bb <- qbbox(lat = shp[, "Y"], lon = shp[, "X"])
MyMap <- GetMap.bbox(bb$lonR, bb$latR, destfile = "DC.jpg")
PlotPolysOnStaticMap(MyMap,
asp = 1,
shp,
lwd = 2,
col = rgb(0.25, 0.25, 0.25, 0.025),
add = FALSE)
Mapping Polygons and Attributes
Newhaven
rm(list = ls())
data(newhaven)
vacant_shades <- auto.shading(blocks$P_VACANT)
vacant_shades## $breaks
## 20% 40% 60% 80%
## 5.4 7.6 10.0 13.0
##
## $cols
## [1] "#FEE5D9" "#FCAE91" "#FB6A4A" "#DE2D26" "#A50F15"
##
## attr(,"class")
## [1] "shading"choropleth(blocks,
v = blocks$P_VACANT)
choro.legend(533000, 161000,
sh = vacant_shades)
vacant_shades <- auto.shading(blocks$P_VACANT,
n = 7)
choropleth(blocks,
v = blocks$P_VACANT,
shading = vacant_shades)
choro.legend(533000, 161000,
sh = vacant_shades)
vacant_shades <- auto.shading(blocks$P_VACANT,
cols = brewer.pal(5, "Greens"))
choropleth(blocks,
v = blocks$P_VACANT,
shading = vacant_shades)
choro.legend(533000, 161000,
sh = vacant_shades)
vacant_shades <- auto.shading(blocks$P_VACANT,
cutter = rangeCuts,
n = 5,
cols = brewer.pal(5, "Blues"))
choropleth(blocks,
v = blocks$P_VACANT,
shading = vacant_shades)
choro.legend(533000, 161000,
sh = vacant_shades)
vacant_shades## $breaks
## #1 #2 #3 #4
## 7.6 15.0 23.0 30.0
##
## $cols
## [1] "#EFF3FF" "#BDD7E7" "#6BAED6" "#3182BD" "#08519C"
##
## attr(,"class")
## [1] "shading"Codes
choropleth## function (sp, v, shading = auto.shading(v), ...)
## {
## i = shading$cols[1 + findInterval(v, shading$breaks)]
## plot(sp, col = i, ...)
## }
## <environment: namespace:GISTools>auto.shading## function (x, digits = 2, cutter = quantileCuts, n = 5, params = NA,
## cols = brewer.pal(n, "Reds"))
## {
## brk = cutter(x, n = n, params = params)
## if (!is.na(digits))
## brk = signif(brk, digits = digits)
## brk = sort(brk)
## brk = brk[!duplicated(brk)]
## res = list(breaks = brk, cols = cols)
## class(res) = "shading"
## res
## }
## <environment: namespace:GISTools>Mapping Points and Attributes
plot(breach)
plot(blocks)
plot(breach,
add = TRUE)
plot(blocks)
plot(breach,
add = TRUE,
pch = '@')
plot(blocks)
plot(breach,
add = TRUE,
pch = 16)
plot(blocks)
plot(breach,
add = TRUE,
pch = 1,
col = "red")
brewer.pal(5, "Reds")## [1] "#FEE5D9" "#FCAE91" "#FB6A4A" "#DE2D26" "#A50F15"pie(rep(1, 5), col = brewer.pal(5, "Reds"))
add.alpha(brewer.pal(5, "Reds"), .50)## [1] "#FEE5D980" "#FCAE9180" "#FB6A4A80" "#DE2D2680" "#A50F1580"plot(blocks)
plot(breach,
add = TRUE,
pch = 1,
col = "#DE2D2680")
Quakes
data(quakes)
head(quakes)## lat long depth mag stations
## 1 -20.42 181.62 562 4.8 41
## 2 -20.62 181.03 650 4.2 15
## 3 -26.00 184.10 42 5.4 43
## 4 -17.97 181.66 626 4.1 19
## 5 -20.42 181.96 649 4.0 11
## 6 -19.68 184.31 195 4.0 12class(quakes)## [1] "data.frame"coords_quakes <- cbind(long = quakes$long,
lat = quakes$lat)
str(coords_quakes)## num [1:1000, 1:2] 182 181 184 182 182 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr [1:2] "long" "lat"#> SpatialPointDataFrame 만들기
quakes_spdf <- SpatialPointsDataFrame(coords_quakes, data = data.frame(quakes))
par(mfrow = c(1, 2))
plot(quakes_spdf)
plot(quakes_spdf, pch = 1, col = '#FB6A4A80')
par(mfrow = c(1, 1))
library(maps)##
## Attaching package: 'maps'## The following object is masked from 'package:purrr':
##
## map## The following object is masked from 'package:GISTools':
##
## map.scaleplot(quakes_spdf, pch = 1, col = '#FB6A4A80')
map('world2', fill = FALSE, add = TRUE)
georgia.polys
data(georgia)
class(georgia.polys)## [1] "list"summary(georgia.polys)## Length Class Mode
## [1,] 250 -none- numeric
## [2,] 198 -none- numeric
## [3,] 106 -none- numeric
## [4,] 248 -none- numeric
## [5,] 232 -none- numeric
## [6,] 114 -none- numeric
## [7,] 176 -none- numeric
## [8,] 96 -none- numeric
## [9,] 138 -none- numeric
## [10,] 320 -none- numeric
## [11,] 214 -none- numeric
## [12,] 52 -none- numeric
## [13,] 326 -none- numeric
## [14,] 302 -none- numeric
## [15,] 574 -none- numeric
## [16,] 380 -none- numeric
## [17,] 272 -none- numeric
## [18,] 154 -none- numeric
## [19,] 186 -none- numeric
## [20,] 454 -none- numeric
## [21,] 74 -none- numeric
## [22,] 112 -none- numeric
## [23,] 60 -none- numeric
## [24,] 512 -none- numeric
## [25,] 360 -none- numeric
## [26,] 192 -none- numeric
## [27,] 64 -none- numeric
## [28,] 94 -none- numeric
## [29,] 136 -none- numeric
## [30,] 136 -none- numeric
## [31,] 146 -none- numeric
## [32,] 128 -none- numeric
## [33,] 118 -none- numeric
## [34,] 184 -none- numeric
## [35,] 134 -none- numeric
## [36,] 174 -none- numeric
## [37,] 230 -none- numeric
## [38,] 216 -none- numeric
## [39,] 234 -none- numeric
## [40,] 86 -none- numeric
## [41,] 28 -none- numeric
## [42,] 112 -none- numeric
## [43,] 100 -none- numeric
## [44,] 108 -none- numeric
## [45,] 182 -none- numeric
## [46,] 134 -none- numeric
## [47,] 96 -none- numeric
## [48,] 88 -none- numeric
## [49,] 178 -none- numeric
## [50,] 116 -none- numeric
## [51,] 410 -none- numeric
## [52,] 250 -none- numeric
## [53,] 266 -none- numeric
## [54,] 112 -none- numeric
## [55,] 146 -none- numeric
## [56,] 222 -none- numeric
## [57,] 142 -none- numeric
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## [69,] 190 -none- numeric
## [70,] 250 -none- numeric
## [71,] 34 -none- numeric
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## [75,] 238 -none- numeric
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## [78,] 188 -none- numeric
## [79,] 144 -none- numeric
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## [82,] 52 -none- numeric
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## [86,] 108 -none- numeric
## [87,] 144 -none- numeric
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## [89,] 442 -none- numeric
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## [99,] 164 -none- numeric
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## [109,] 256 -none- numeric
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## [113,] 374 -none- numeric
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## [156,] 232 -none- numeric
## [157,] 274 -none- numeric
## [158,] 242 -none- numeric
## [159,] 204 -none- numericstr(georgia.polys)## List of 159
## $ : num [1:125, 1:2] 1292287 1292654 1292949 1294045 1294603 ...
## $ : num [1:99, 1:2] 1263206 1264530 1263799 1263714 1263095 ...
## $ : num [1:53, 1:2] 1267843 1270202 1271306 1272213 1272824 ...
## $ : num [1:124, 1:2] 1120149 1120164 1119692 1119295 1118798 ...
## $ : num [1:116, 1:2] 1175513 1177004 1192290 1192624 1192486 ...
## $ : num [1:57, 1:2] 1145286 1147147 1147695 1147509 1147702 ...
## $ : num [1:88, 1:2] 1139961 1139952 1130886 1129920 1129514 ...
## $ : num [1:48, 1:2] 1032460 1033151 1034035 1034110 1033265 ...
## $ : num [1:69, 1:2] 1204456 1205348 1206102 1206600 1207069 ...
## $ : num [1:160, 1:2] 1213059 1213172 1212754 1212907 1213424 ...
## $ : num [1:107, 1:2] 1123543 1130095 1133489 1137617 1137047 ...
## $ : num [1:26, 1:2] 1188893 1199421 1195803 1185260 1187452 ...
## $ : num [1:163, 1:2] 1347952 1348302 1348082 1347279 1346895 ...
## $ : num [1:151, 1:2] 1163881 1179257 1178518 1179108 1179011 ...
## $ : num [1:287, 1:2] 1360177 1360720 1361011 1360864 1361293 ...
## $ : num [1:190, 1:2] 1315860 1316107 1316888 1317934 1318723 ...
## $ : num [1:136, 1:2] 1304940 1305548 1307061 1307467 1309244 ...
## $ : num [1:77, 1:2] 1118825 1119066 1119566 1119167 1121554 ...
## $ : num [1:93, 1:2] 1088588 1089134 1088424 1089111 1089154 ...
## $ : num [1:227, 1:2] 1333407 1333712 1333271 1333628 1333119 ...
## $ : num [1:37, 1:2] 1300215 1306107 1305910 1305934 1305511 ...
## $ : num [1:56, 1:2] 1018187 1018834 1017997 1018011 1018097 ...
## $ : num [1:30, 1:2] 995434 995645 994050 994430 993887 ...
## $ : num [1:256, 1:2] 1315560 1320365 1321194 1333407 1334119 ...
## $ : num [1:180, 1:2] 1366749 1382496 1387451 1386801 1388059 ...
## $ : num [1:96, 1:2] 1058913 1059361 1057588 1060919 1047574 ...
## $ : num [1:32, 1:2] 989052 987992 986368 985657 985105 ...
## $ : num [1:47, 1:2] 1068729 1069256 1071279 1064966 1064189 ...
## $ : num [1:68, 1:2] 1164824 1164115 1164104 1163595 1164489 ...
## $ : num [1:68, 1:2] 1038886 1039654 1040586 1040981 1041848 ...
## $ : num [1:73, 1:2] 1076638 1076740 1077620 1077721 1078582 ...
## $ : num [1:64, 1:2] 1262010 1272080 1272522 1273357 1274083 ...
## $ : num [1:59, 1:2] 1029201 1036370 1039497 1039561 1040472 ...
## $ : num [1:92, 1:2] 1236803 1238991 1258555 1260244 1263257 ...
## $ : num [1:67, 1:2] 1180769 1180913 1181429 1181524 1182013 ...
## $ : num [1:87, 1:2] 1264293 1265492 1266277 1266521 1267204 ...
## $ : num [1:115, 1:2] 1187811 1188233 1187860 1188054 1187871 ...
## $ : num [1:108, 1:2] 1048587 1048052 1047461 1047758 1047537 ...
## $ : num [1:117, 1:2] 1123543 1123870 1125238 1125548 1126286 ...
## $ : num [1:43, 1:2] 1161518 1163783 1164470 1146712 1145790 ...
## $ : num [1:14, 1:2] 960827 960251 956009 955029 955940 ...
## $ : num [1:56, 1:2] 1071887 1071728 1072304 1080546 1081978 ...
## $ : num [1:50, 1:2] 1102905 1104749 1107760 1098833 1061672 ...
## $ : num [1:54, 1:2] 1098712 1096077 1092233 1092201 1090964 ...
## $ : num [1:91, 1:2] 1199421 1217335 1226228 1226459 1227872 ...
## $ : num [1:67, 1:2] 1157182 1158036 1158127 1158577 1157712 ...
## $ : num [1:48, 1:2] 1102889 1126736 1126850 1127320 1127690 ...
## $ : num [1:44, 1:2] 1033955 1043582 1043410 1048227 1047625 ...
## $ : num [1:89, 1:2] 1055504 1055634 1056842 1056694 1057683 ...
## $ : num [1:58, 1:2] 1234343 1234760 1234918 1235370 1236656 ...
## $ : num [1:205, 1:2] 1369072 1369386 1369271 1369873 1369909 ...
## $ : num [1:125, 1:2] 1177797 1183012 1184785 1185896 1185284 ...
## $ : num [1:133, 1:2] 1285172 1293325 1301756 1300262 1300215 ...
## $ : num [1:56, 1:2] 1310313 1310484 1310843 1311737 1314887 ...
## $ : num [1:73, 1:2] 1054566 1071855 1070760 1070285 1070016 ...
## $ : num [1:111, 1:2] 1061744 1063484 1064200 1064394 1065808 ...
## $ : num [1:71, 1:2] 992544 992688 993153 993629 991241 ...
## $ : num [1:72, 1:2] 1069256 1096565 1097688 1097739 1097307 ...
## $ : num [1:54, 1:2] 1170770 1170964 1171820 1172635 1173287 ...
## $ : num [1:150, 1:2] 1058286 1057847 1058185 1058508 1059555 ...
## $ : num [1:97, 1:2] 1070923 1070663 1069911 1069496 1069192 ...
## $ : num [1:64, 1:2] 1251398 1239001 1239358 1239991 1240309 ...
## $ : num [1:138, 1:2] 1347952 1348601 1349930 1350460 1350463 ...
## $ : num [1:75, 1:2] 1005967 1006474 1006715 1010723 1010827 ...
## $ : num [1:25, 1:2] 1102905 1127427 1128414 1128890 1128762 ...
## $ : num [1:105, 1:2] 1155854 1165814 1165155 1165192 1165589 ...
## $ : num [1:74, 1:2] 1112155 1109239 1110645 1112386 1113099 ...
## $ : num [1:125, 1:2] 1117103 1117373 1118258 1119095 1119598 ...
## $ : num [1:95, 1:2] 1104431 1109396 1109259 1110258 1110377 ...
## $ : num [1:125, 1:2] 1210300 1211423 1211627 1212028 1212128 ...
## $ : num [1:17, 1:2] 1003022 1004268 1005342 1004296 1005409 ...
## $ : num [1:73, 1:2] 1033689 1034990 1035053 1035665 1043933 ...
## $ : num [1:57, 1:2] 1176087 1177791 1178268 1180708 1181536 ...
## $ : num [1:22, 1:2] 986797 1012381 1019505 1019442 1020341 ...
## $ : num [1:119, 1:2] 1076638 1080088 1080307 1081995 1081781 ...
## $ : num [1:155, 1:2] 1143436 1143422 1146977 1148476 1150074 ...
## $ : num [1:60, 1:2] 1180061 1187796 1187656 1190495 1190664 ...
## $ : num [1:94, 1:2] 1127656 1128002 1129884 1130496 1133580 ...
## $ : num [1:72, 1:2] 1148060 1148275 1148661 1148728 1150824 ...
## $ : num [1:97, 1:2] 1272207 1274255 1265956 1267370 1264520 ...
## $ : num [1:109, 1:2] 1257970 1259081 1260114 1260995 1262022 ...
## $ : num [1:26, 1:2] 1318306 1312852 1313326 1314522 1314739 ...
## $ : num [1:58, 1:2] 1250375 1251704 1252449 1253825 1255489 ...
## $ : num [1:42, 1:2] 1150824 1160389 1160971 1161313 1163673 ...
## $ : num [1:17, 1:2] 1097238 1104802 1108129 1107254 1107431 ...
## $ : num [1:54, 1:2] 1226717 1233822 1238599 1237436 1236656 ...
## $ : num [1:72, 1:2] 1188893 1204709 1211929 1220520 1228059 ...
## $ : num [1:76, 1:2] 1133983 1133276 1133320 1133781 1133331 ...
## $ : num [1:221, 1:2] 1333189 1336515 1336762 1336895 1337737 ...
## $ : num [1:99, 1:2] 1220666 1221242 1221480 1222027 1222117 ...
## $ : num [1:150, 1:2] 1318149 1317916 1317679 1317023 1316846 ...
## $ : num [1:176, 1:2] 1188569 1205677 1214880 1216488 1217729 ...
## $ : num [1:106, 1:2] 1074049 1074331 1074532 1074932 1075141 ...
## $ : num [1:117, 1:2] 1241266 1241423 1242286 1242690 1243154 ...
## $ : num [1:143, 1:2] 1394263 1393253 1392470 1388469 1388156 ...
## $ : num [1:75, 1:2] 1113237 1113319 1115117 1115361 1116923 ...
## $ : num [1:126, 1:2] 1173889 1173840 1177797 1177804 1177419 ...
## $ : num [1:74, 1:2] 1076440 1076774 1075883 1075999 1076920 ...
## $ : num [1:82, 1:2] 1029476 1030403 1029973 1042605 1042508 ...
## [list output truncated]tmp <- georgia.polys[c(1, 3, 151, 113)]
t1 <- Polygon(tmp[1]); t1 <- Polygons(list(t1), "1")
t2 <- Polygon(tmp[2]); t2 <- Polygons(list(t2), "2")
t3 <- Polygon(tmp[3]); t3 <- Polygons(list(t3), "3")
t4 <- Polygon(tmp[4]); t4 <- Polygons(list(t4), "4")
tmp_Sp <- SpatialPolygons(list(t1, t2, t3, t4), 1:4)
plot(tmp_Sp)
names <- c("Appling", "Bacon", "Wayne", "Pierce")
tmp_spdf <- SpatialPolygonsDataFrame(tmp_Sp, data = data.frame(names))
data.frame(tmp_spdf)## names
## 1 Appling
## 2 Bacon
## 3 Wayne
## 4 Piercetmp_spdf@data## names
## 1 Appling
## 2 Bacon
## 3 Wayne
## 4 Pierceplot(tmp_spdf, col = 2:5)
quakes
par(mfrow = c(2, 2))
choropleth(quakes_spdf,
v = quakes$mag)
shades <- auto.shading(quakes$mag,
n = 6,
cols = brewer.pal(6, "Greens"))
str(shades)## List of 2
## $ breaks: Named num [1:5] 4.2 4.4 4.6 4.7 5
## ..- attr(*, "names")= chr [1:5] "16.66667%" "33.33333%" "50%" "66.66667%" ...
## $ cols : chr [1:6] "#EDF8E9" "#C7E9C0" "#A1D99B" "#74C476" ...
## - attr(*, "class")= chr "shading"choropleth(quakes_spdf,
v = quakes$mag,
shading = shades,
pch = 1)
shades$cols <- add.alpha(shades$cols, 0.5)
choropleth(quakes_spdf,
v = quakes$mag,
shading = shades,
pch = 20)
mag_z <- (quakes$mag - min(quakes$mag)) / max(quakes$mag)
plot(quakes_spdf,
cex = mag_z * 3,
pch = 1,
col = '#FB6A4A80')
par(mfrow = c(1, 1))par(mfrow = c(1, 2))
tmp2 <- cut(quakes$mag,
fivenum(quakes$mag),
include.lowest = TRUE)
str(tmp2)## Factor w/ 4 levels "[4,4.3]","(4.3,4.6]",..: 3 1 4 1 1 1 3 2 3 1 ...class_mag <- match(tmp2, levels(tmp2))
str(class_mag)## int [1:1000] 3 1 4 1 1 1 3 2 3 1 ...pch_var <- c(0, 1, 2, 5)
plot(quakes_spdf,
pch = pch_var[class_mag],
cex = 0.7,
col = '#252525B3')
index_1 <- (quakes$mag >= 4 & quakes$mag < 5) + 0
index_2 <- (quakes$mag >= 5 & quakes$mag < 5.5) * 2
index_3 <- (quakes$mag >= 5.5) * 3
cbind(index_1, index_2, index_3)## index_1 index_2 index_3
## [1,] 1 0 0
## [2,] 1 0 0
## [3,] 0 2 0
## [4,] 1 0 0
## [5,] 1 0 0
## [6,] 1 0 0
## [7,] 1 0 0
## [8,] 1 0 0
## [9,] 1 0 0
## [10,] 1 0 0
## [11,] 1 0 0
## [12,] 1 0 0
## [13,] 1 0 0
## [14,] 1 0 0
## [15,] 0 0 3
## [16,] 1 0 0
## [17,] 0 0 3
## [18,] 1 0 0
## [19,] 1 0 0
## [20,] 1 0 0
## [21,] 1 0 0
## [22,] 1 0 0
## [23,] 1 0 0
## [24,] 1 0 0
## [25,] 0 2 0
## [26,] 1 0 0
## [27,] 1 0 0
## [28,] 0 2 0
## [29,] 1 0 0
## [30,] 1 0 0
## [31,] 1 0 0
## [32,] 1 0 0
## [33,] 1 0 0
## [34,] 1 0 0
## [35,] 1 0 0
## [36,] 1 0 0
## [37,] 1 0 0
## [38,] 1 0 0
## [39,] 1 0 0
## [40,] 1 0 0
## [41,] 1 0 0
## [42,] 1 0 0
## [43,] 1 0 0
## [44,] 1 0 0
## [45,] 1 0 0
## [46,] 1 0 0
## [47,] 1 0 0
## [48,] 1 0 0
## [49,] 1 0 0
## [50,] 0 2 0
## [51,] 1 0 0
## [52,] 1 0 0
## [53,] 1 0 0
## [54,] 1 0 0
## [55,] 1 0 0
## [56,] 1 0 0
## [57,] 1 0 0
## [58,] 1 0 0
## [59,] 1 0 0
## [60,] 1 0 0
## [61,] 1 0 0
## [62,] 1 0 0
## [63,] 0 2 0
## [64,] 1 0 0
## [65,] 1 0 0
## [66,] 1 0 0
## [67,] 1 0 0
## [68,] 0 2 0
## [69,] 1 0 0
## [70,] 0 0 3
## [71,] 1 0 0
## [72,] 1 0 0
## [73,] 1 0 0
## [74,] 0 2 0
## [75,] 1 0 0
## [76,] 1 0 0
## [77,] 1 0 0
## [78,] 1 0 0
## [79,] 1 0 0
## [80,] 0 2 0
## [81,] 0 2 0
## [82,] 1 0 0
## [83,] 1 0 0
## [84,] 1 0 0
## [85,] 1 0 0
## [86,] 1 0 0
## [87,] 1 0 0
## [88,] 1 0 0
## [89,] 1 0 0
## [90,] 1 0 0
## [91,] 0 2 0
## [92,] 1 0 0
## [93,] 0 2 0
## [94,] 1 0 0
## [95,] 1 0 0
## [96,] 1 0 0
## [97,] 1 0 0
## [98,] 0 2 0
## [99,] 0 2 0
## [100,] 1 0 0
## [101,] 1 0 0
## [102,] 1 0 0
## [103,] 1 0 0
## [104,] 1 0 0
## [105,] 1 0 0
## [106,] 1 0 0
## [107,] 1 0 0
## [108,] 1 0 0
## [109,] 0 0 3
## [110,] 0 2 0
## [111,] 1 0 0
## [112,] 1 0 0
## [113,] 1 0 0
## [114,] 1 0 0
## [115,] 1 0 0
## [116,] 1 0 0
## [117,] 0 2 0
## [118,] 1 0 0
## [119,] 1 0 0
## [120,] 1 0 0
## [121,] 1 0 0
## [122,] 1 0 0
## [123,] 1 0 0
## [124,] 1 0 0
## [125,] 1 0 0
## [126,] 0 2 0
## [127,] 1 0 0
## [128,] 0 2 0
## [129,] 1 0 0
## [130,] 1 0 0
## [131,] 1 0 0
## [132,] 1 0 0
## [133,] 1 0 0
## [134,] 1 0 0
## [135,] 1 0 0
## [136,] 1 0 0
## [137,] 0 2 0
## [138,] 1 0 0
## [139,] 1 0 0
## [140,] 1 0 0
## [141,] 1 0 0
## [142,] 1 0 0
## [143,] 0 2 0
## [144,] 1 0 0
## [145,] 1 0 0
## [146,] 1 0 0
## [147,] 1 0 0
## [148,] 1 0 0
## [149,] 0 2 0
## [150,] 1 0 0
## [151,] 0 0 3
## [152,] 0 0 3
## [153,] 1 0 0
## [154,] 1 0 0
## [155,] 1 0 0
## [156,] 1 0 0
## [157,] 1 0 0
## [158,] 1 0 0
## [159,] 1 0 0
## [160,] 1 0 0
## [161,] 1 0 0
## [162,] 1 0 0
## [163,] 1 0 0
## [164,] 1 0 0
## [165,] 1 0 0
## [166,] 0 2 0
## [167,] 0 0 3
## [168,] 0 2 0
## [169,] 1 0 0
## [170,] 1 0 0
## [171,] 1 0 0
## [172,] 1 0 0
## [173,] 1 0 0
## [174,] 1 0 0
## [175,] 1 0 0
## [176,] 0 0 3
## [177,] 0 2 0
## [178,] 1 0 0
## [179,] 1 0 0
## [180,] 1 0 0
## [181,] 1 0 0
## [182,] 1 0 0
## [183,] 1 0 0
## [184,] 1 0 0
## [185,] 1 0 0
## [186,] 1 0 0
## [187,] 1 0 0
## [188,] 1 0 0
## [189,] 1 0 0
## [190,] 1 0 0
## [191,] 0 2 0
## [192,] 1 0 0
## [193,] 1 0 0
## [194,] 1 0 0
## [195,] 1 0 0
## [196,] 1 0 0
## [197,] 1 0 0
## [198,] 1 0 0
## [199,] 1 0 0
## [200,] 0 2 0
## [201,] 1 0 0
## [202,] 1 0 0
## [203,] 1 0 0
## [204,] 1 0 0
## [205,] 1 0 0
## [206,] 1 0 0
## [207,] 0 2 0
## [208,] 1 0 0
## [209,] 1 0 0
## [210,] 1 0 0
## [211,] 1 0 0
## [212,] 1 0 0
## [213,] 1 0 0
## [214,] 0 2 0
## [215,] 1 0 0
## [216,] 1 0 0
## [217,] 1 0 0
## [218,] 1 0 0
## [219,] 1 0 0
## [220,] 1 0 0
## [221,] 1 0 0
## [222,] 1 0 0
## [223,] 1 0 0
## [224,] 1 0 0
## [225,] 1 0 0
## [226,] 1 0 0
## [227,] 1 0 0
## [228,] 1 0 0
## [229,] 0 2 0
## [230,] 0 2 0
## [231,] 1 0 0
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## [233,] 1 0 0
## [234,] 1 0 0
## [235,] 1 0 0
## [236,] 1 0 0
## [237,] 1 0 0
## [238,] 0 2 0
## [239,] 1 0 0
## [240,] 1 0 0
## [241,] 1 0 0
## [242,] 1 0 0
## [243,] 0 2 0
## [244,] 1 0 0
## [245,] 0 2 0
## [246,] 1 0 0
## [247,] 1 0 0
## [248,] 1 0 0
## [249,] 0 2 0
## [250,] 1 0 0
## [251,] 1 0 0
## [252,] 1 0 0
## [253,] 0 2 0
## [254,] 1 0 0
## [255,] 1 0 0
## [256,] 1 0 0
## [257,] 1 0 0
## [258,] 1 0 0
## [259,] 1 0 0
## [260,] 1 0 0
## [261,] 0 2 0
## [262,] 1 0 0
## [263,] 1 0 0
## [264,] 1 0 0
## [265,] 1 0 0
## [266,] 1 0 0
## [267,] 1 0 0
## [268,] 1 0 0
## [269,] 1 0 0
## [270,] 1 0 0
## [271,] 1 0 0
## [272,] 1 0 0
## [273,] 1 0 0
## [274,] 1 0 0
## [275,] 0 0 3
## [276,] 1 0 0
## [277,] 0 2 0
## [278,] 1 0 0
## [279,] 1 0 0
## [280,] 0 2 0
## [281,] 1 0 0
## [282,] 1 0 0
## [283,] 1 0 0
## [284,] 1 0 0
## [285,] 1 0 0
## [286,] 1 0 0
## [287,] 1 0 0
## [288,] 1 0 0
## [289,] 1 0 0
## [290,] 0 2 0
## [291,] 0 2 0
## [292,] 1 0 0
## [293,] 1 0 0
## [294,] 1 0 0
## [295,] 0 2 0
## [296,] 0 2 0
## [297,] 0 0 3
## [298,] 1 0 0
## [299,] 1 0 0
## [300,] 1 0 0
## [301,] 1 0 0
## [302,] 1 0 0
## [303,] 1 0 0
## [304,] 1 0 0
## [305,] 1 0 0
## [306,] 1 0 0
## [307,] 1 0 0
## [308,] 1 0 0
## [309,] 1 0 0
## [310,] 1 0 0
## [311,] 1 0 0
## [312,] 0 2 0
## [313,] 0 2 0
## [314,] 1 0 0
## [315,] 1 0 0
## [316,] 1 0 0
## [317,] 1 0 0
## [318,] 0 2 0
## [319,] 1 0 0
## [320,] 1 0 0
## [321,] 1 0 0
## [322,] 0 2 0
## [323,] 1 0 0
## [324,] 1 0 0
## [325,] 1 0 0
## [326,] 1 0 0
## [327,] 1 0 0
## [328,] 1 0 0
## [329,] 1 0 0
## [330,] 0 2 0
## [331,] 0 2 0
## [332,] 1 0 0
## [333,] 1 0 0
## [334,] 0 2 0
## [335,] 0 2 0
## [336,] 1 0 0
## [337,] 1 0 0
## [338,] 0 2 0
## [339,] 1 0 0
## [340,] 1 0 0
## [341,] 1 0 0
## [342,] 1 0 0
## [343,] 1 0 0
## [344,] 1 0 0
## [345,] 1 0 0
## [346,] 1 0 0
## [347,] 1 0 0
## [348,] 1 0 0
## [349,] 0 2 0
## [350,] 1 0 0
## [351,] 1 0 0
## [352,] 1 0 0
## [353,] 1 0 0
## [354,] 0 0 3
## [355,] 1 0 0
## [356,] 0 2 0
## [357,] 0 2 0
## [358,] 0 0 3
## [359,] 1 0 0
## [360,] 1 0 0
## [361,] 1 0 0
## [362,] 1 0 0
## [363,] 0 2 0
## [364,] 1 0 0
## [365,] 1 0 0
## [366,] 1 0 0
## [367,] 0 2 0
## [368,] 1 0 0
## [369,] 1 0 0
## [370,] 1 0 0
## [371,] 0 2 0
## [372,] 0 2 0
## [373,] 0 2 0
## [374,] 0 2 0
## [375,] 1 0 0
## [376,] 0 0 3
## [377,] 1 0 0
## [378,] 0 2 0
## [379,] 1 0 0
## [380,] 0 0 3
## [381,] 0 2 0
## [382,] 1 0 0
## [383,] 0 2 0
## [384,] 0 2 0
## [385,] 0 2 0
## [386,] 0 2 0
## [387,] 1 0 0
## [388,] 1 0 0
## [389,] 1 0 0
## [390,] 1 0 0
## [391,] 1 0 0
## [392,] 1 0 0
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## [394,] 1 0 0
## [395,] 1 0 0
## [396,] 1 0 0
## [397,] 0 2 0
## [398,] 0 2 0
## [399,] 0 0 3
## [400,] 0 2 0
## [401,] 1 0 0
## [402,] 1 0 0
## [403,] 1 0 0
## [404,] 0 2 0
## [405,] 1 0 0
## [406,] 1 0 0
## [407,] 1 0 0
## [408,] 1 0 0
## [409,] 1 0 0
## [410,] 1 0 0
## [411,] 1 0 0
## [412,] 1 0 0
## [413,] 1 0 0
## [414,] 1 0 0
## [415,] 1 0 0
## [416,] 0 2 0
## [417,] 1 0 0
## [418,] 1 0 0
## [419,] 1 0 0
## [420,] 1 0 0
## [421,] 1 0 0
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## [423,] 1 0 0
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## [425,] 1 0 0
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## [427,] 1 0 0
## [428,] 1 0 0
## [429,] 1 0 0
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## [431,] 1 0 0
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## [433,] 1 0 0
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## [435,] 1 0 0
## [436,] 1 0 0
## [437,] 1 0 0
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## [440,] 1 0 0
## [441,] 1 0 0
## [442,] 1 0 0
## [443,] 1 0 0
## [444,] 1 0 0
## [445,] 0 2 0
## [446,] 1 0 0
## [447,] 1 0 0
## [448,] 0 2 0
## [449,] 0 0 3
## [450,] 1 0 0
## [451,] 1 0 0
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## [454,] 1 0 0
## [455,] 1 0 0
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## [458,] 1 0 0
## [459,] 0 2 0
## [460,] 1 0 0
## [461,] 1 0 0
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## [463,] 0 2 0
## [464,] 1 0 0
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## [466,] 1 0 0
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## [478,] 1 0 0
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## [480,] 1 0 0
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## [482,] 1 0 0
## [483,] 1 0 0
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## [485,] 1 0 0
## [486,] 0 2 0
## [487,] 1 0 0
## [488,] 1 0 0
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## [490,] 1 0 0
## [491,] 1 0 0
## [492,] 1 0 0
## [493,] 1 0 0
## [494,] 1 0 0
## [495,] 1 0 0
## [496,] 0 0 3
## [497,] 1 0 0
## [498,] 1 0 0
## [499,] 1 0 0
## [500,] 1 0 0
## [501,] 1 0 0
## [502,] 1 0 0
## [503,] 1 0 0
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## [532,] 1 0 0
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## [542,] 1 0 0
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## [559,] 1 0 0
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## [565,] 1 0 0
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## [810,] 1 0 0
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## [813,] 1 0 0
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## [822,] 1 0 0
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## [826,] 1 0 0
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## [840,] 0 2 0
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## [842,] 1 0 0
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## [844,] 0 2 0
## [845,] 1 0 0
## [846,] 1 0 0
## [847,] 1 0 0
## [848,] 1 0 0
## [849,] 0 2 0
## [850,] 0 2 0
## [851,] 1 0 0
## [852,] 1 0 0
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## [856,] 1 0 0
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## [861,] 1 0 0
## [862,] 1 0 0
## [863,] 1 0 0
## [864,] 1 0 0
## [865,] 1 0 0
## [866,] 1 0 0
## [867,] 1 0 0
## [868,] 1 0 0
## [869,] 0 0 3
## [870,] 0 0 3
## [871,] 1 0 0
## [872,] 1 0 0
## [873,] 1 0 0
## [874,] 1 0 0
## [875,] 1 0 0
## [876,] 1 0 0
## [877,] 1 0 0
## [878,] 1 0 0
## [879,] 1 0 0
## [880,] 1 0 0
## [881,] 1 0 0
## [882,] 1 0 0
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## [884,] 1 0 0
## [885,] 0 2 0
## [886,] 1 0 0
## [887,] 1 0 0
## [888,] 0 2 0
## [889,] 0 2 0
## [890,] 0 2 0
## [891,] 1 0 0
## [892,] 1 0 0
## [893,] 0 0 3
## [894,] 1 0 0
## [895,] 1 0 0
## [896,] 1 0 0
## [897,] 1 0 0
## [898,] 1 0 0
## [899,] 1 0 0
## [900,] 1 0 0
## [901,] 1 0 0
## [902,] 0 2 0
## [903,] 1 0 0
## [904,] 1 0 0
## [905,] 1 0 0
## [906,] 1 0 0
## [907,] 1 0 0
## [908,] 0 2 0
## [909,] 1 0 0
## [910,] 0 2 0
## [911,] 1 0 0
## [912,] 1 0 0
## [913,] 1 0 0
## [914,] 1 0 0
## [915,] 1 0 0
## [916,] 0 2 0
## [917,] 1 0 0
## [918,] 1 0 0
## [919,] 1 0 0
## [920,] 0 0 3
## [921,] 0 2 0
## [922,] 0 2 0
## [923,] 1 0 0
## [924,] 1 0 0
## [925,] 0 2 0
## [926,] 1 0 0
## [927,] 1 0 0
## [928,] 0 2 0
## [929,] 1 0 0
## [930,] 1 0 0
## [931,] 1 0 0
## [932,] 1 0 0
## [933,] 1 0 0
## [934,] 1 0 0
## [935,] 0 0 3
## [936,] 0 2 0
## [937,] 1 0 0
## [938,] 0 2 0
## [939,] 1 0 0
## [940,] 1 0 0
## [941,] 1 0 0
## [942,] 1 0 0
## [943,] 1 0 0
## [944,] 0 2 0
## [945,] 1 0 0
## [946,] 1 0 0
## [947,] 1 0 0
## [948,] 0 0 3
## [949,] 1 0 0
## [950,] 1 0 0
## [951,] 1 0 0
## [952,] 0 0 3
## [953,] 1 0 0
## [954,] 1 0 0
## [955,] 1 0 0
## [956,] 1 0 0
## [957,] 1 0 0
## [958,] 1 0 0
## [959,] 1 0 0
## [960,] 1 0 0
## [961,] 1 0 0
## [962,] 1 0 0
## [963,] 1 0 0
## [964,] 1 0 0
## [965,] 0 2 0
## [966,] 1 0 0
## [967,] 1 0 0
## [968,] 1 0 0
## [969,] 1 0 0
## [970,] 0 2 0
## [971,] 1 0 0
## [972,] 0 2 0
## [973,] 1 0 0
## [974,] 1 0 0
## [975,] 1 0 0
## [976,] 1 0 0
## [977,] 1 0 0
## [978,] 1 0 0
## [979,] 1 0 0
## [980,] 1 0 0
## [981,] 0 2 0
## [982,] 1 0 0
## [983,] 1 0 0
## [984,] 1 0 0
## [985,] 1 0 0
## [986,] 1 0 0
## [987,] 0 2 0
## [988,] 1 0 0
## [989,] 1 0 0
## [990,] 1 0 0
## [991,] 1 0 0
## [992,] 1 0 0
## [993,] 1 0 0
## [994,] 1 0 0
## [995,] 1 0 0
## [996,] 1 0 0
## [997,] 1 0 0
## [998,] 1 0 0
## [999,] 1 0 0
## [1000,] 0 0 3class_mag2 <- index_1 + index_2 + index_3
class_mag2## [1] 1 1 2 1 1 1 1 1 1 1 1 1 1 1 3 1 3 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 1 1
## [35] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2
## [69] 1 3 1 1 1 2 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 2 2 1 1 1
## [103] 1 1 1 1 1 1 3 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1
## [137] 2 1 1 1 1 1 2 1 1 1 1 1 2 1 3 3 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 2 1 1
## [171] 1 1 1 1 1 3 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1
## [205] 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 2
## [239] 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1
## [273] 1 1 3 1 2 1 1 2 1 1 1 1 1 1 1 1 1 2 2 1 1 1 2 2 3 1 1 1 1 1 1 1 1 1
## [307] 1 1 1 1 1 2 2 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 2 1 1 2 2 1 1 2 1 1
## [341] 1 1 1 1 1 1 1 1 2 1 1 1 1 3 1 2 2 3 1 1 1 1 2 1 1 1 2 1 1 1 2 2 2 2
## [375] 1 3 1 2 1 3 2 1 2 2 2 2 1 1 1 1 1 1 1 1 1 1 2 2 3 2 1 1 1 2 1 1 1 1
## [409] 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [443] 1 1 2 1 1 2 3 1 1 1 1 1 1 1 1 1 2 1 1 2 2 1 2 1 1 1 1 1 1 1 1 2 1 1
## [477] 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [511] 1 3 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 2 1 1 3 1 1 1 1 1 1 1 2 1 3 1 1 1
## [545] 1 1 2 1 2 1 1 1 1 1 1 1 1 3 1 1 1 1 1 2 1 1 1 2 1 3 2 1 1 2 1 1 1 1
## [579] 2 2 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 3 1 1 1 1 1 1 1
## [613] 1 1 2 1 1 2 1 1 1 1 2 2 1 1 1 1 2 1 1 1 1 1 1 3 1 2 1 1 1 1 2 1 1 1
## [647] 1 1 3 1 2 1 3 1 1 1 2 1 1 1 1 1 3 2 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1
## [681] 2 1 1 1 1 1 1 1 2 1 1 2 1 1 1 1 2 1 1 2 1 2 2 1 1 1 1 2 1 1 1 3 1 2
## [715] 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 1 1
## [749] 1 1 1 2 3 1 1 1 2 2 2 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1
## [783] 2 1 2 1 2 2 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1
## [817] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 2 2 1 1 1 1 2 2
## [851] 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 3 1 1 1 1 1 1 1 1 1 1 1 1 2 1
## [885] 2 1 1 2 2 2 1 1 3 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1
## [919] 1 3 2 2 1 1 2 1 1 2 1 1 1 1 1 1 3 2 1 2 1 1 1 1 1 2 1 1 1 3 1 1 1 3
## [953] 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1
## [987] 2 1 1 1 1 1 1 1 1 1 1 1 1 3col_var <- brewer.pal(3, "Blues")
plot(quakes_spdf,
col = col_var[class_mag2],
cex = 1.4,
pch = 20)
par(mfrow = c(1, 1))RgoogleMaps
library(RgoogleMaps)
class(quakes$lat)## [1] "numeric"MyMap <- MapBackground(lat = quakes$lat,
lon = quakes$long,
zoom = 10)## [1] "http://maps.google.com/maps/api/staticmap?center=-24.655,176.9&zoom=4&size=640x640&maptype=mobile&format=png32&sensor=true"
## center, zoom: -24.655 176.9 10PlotOnStaticMap(MyMap,
quakes$lat,
quakes$long,
cex = mag_z + 0.3,
pch = 1,
col = '#FB6A4A80')
MyMap <- MapBackground(lat = quakes$lat,
lon = quakes$long,
zoom = 10,
maptype = "satellite")## [1] "http://maps.google.com/maps/api/staticmap?center=-24.655,176.9&zoom=4&size=640x640&maptype=satellite&format=png32&sensor=true"
## center, zoom: -24.655 176.9 10PlotOnStaticMap(MyMap,
quakes$lat,
quakes$long,
cex = mag_z + 0.3,
pch = 1,
col = '#FB6A4A80')
Mapping Lines and Attributes
data(newhaven)
xmin <- bbox(roads)[1, 1]
ymin <- bbox(roads)[2, 1]
xmax <- xmin + diff(bbox(roads)[1, ]) / 2
# xmax <- bbox(roads)[1, 2]
ymax <- ymin + diff(bbox(roads)[2, ]) / 2
# ymax <- bbox(roads)[2, 2]
xx <- c(xmin, xmin, xmax, xmax, xmin)
yy <- c(ymin, ymax, ymax, ymin, ymin)
crds <- cbind(xx, yy)
Pl <- Polygon(crds)
Pl## An object of class "Polygon"
## Slot "labpt":
## [1] 541191.7 160184.0
##
## Slot "area":
## [1] 352507740
##
## Slot "hole":
## [1] FALSE
##
## Slot "ringDir":
## [1] 1
##
## Slot "coords":
## xx yy
## 531806.2 150794.2
## 531806.2 169573.8
## max 550577.1 169573.8
## max 550577.1 150794.2
## 531806.2 150794.2ID <- "clip"
Pls <- Polygons(list(Pl), ID = ID)
Pls## An object of class "Polygons"
## Slot "Polygons":
## [[1]]
## An object of class "Polygon"
## Slot "labpt":
## [1] 541191.7 160184.0
##
## Slot "area":
## [1] 352507740
##
## Slot "hole":
## [1] FALSE
##
## Slot "ringDir":
## [1] 1
##
## Slot "coords":
## xx yy
## 531806.2 150794.2
## 531806.2 169573.8
## max 550577.1 169573.8
## max 550577.1 150794.2
## 531806.2 150794.2
##
##
##
## Slot "plotOrder":
## [1] 1
##
## Slot "labpt":
## [1] 541191.7 160184.0
##
## Slot "ID":
## [1] "clip"
##
## Slot "area":
## [1] 352507740SPls <- SpatialPolygons(list(Pls))
df <- data.frame(value = 1, row.names = ID)
df## value
## clip 1clip.bb <- SpatialPolygonsDataFrame(SPls, df)
roads_tmp <- gIntersection(clip.bb,
roads,
byid = TRUE)
head(names(roads_tmp))## [1] "clip 2951" "clip 2952" "clip 2959" "clip 2960" "clip 2965" "clip 2972"tmp <- as.numeric(gsub("clip", "", names(roads_tmp)))
tmp <- data.frame(roads)[tmp, ]
head(tmp)## FNODE_ TNODE_ LPOLY_ RPOLY_ LENGTH ROADM_ ROADM_ID AV_LEGEND
## 2950 1978 1973 2 2 280.9774 2951 160745 LOCAL ROAD
## 2951 1979 1972 2 2 662.1912 2952 160761 LOCAL ROAD
## 2958 1870 1983 2 2 887.6739 2959 227941 LOCAL ROAD
## 2959 1984 1962 2 2 315.7033 2960 160779 LOCAL ROAD
## 2964 1987 1686 2 2 2508.8198 2965 160819 LOCAL ROAD
## 2971 1990 1991 2 2 252.7340 2972 160878 LOCAL ROAD
## ROARC_COD PHOTRV_FLG QUAD_NO OVRPAS_COD LIMACC_FLG NO_LANES
## 2950 209 0 0 0 0 0
## 2951 209 0 0 0 0 0
## 2958 217 1 0 0 0 0
## 2959 209 0 0 0 0 0
## 2964 209 0 0 0 0 0
## 2971 209 0 0 0 0 0
## LENGTH_MI DXF_LAYER SPLIT
## 2950 0.05321542 209 0
## 2951 0.12541500 209 0
## 2958 0.16812006 217 0
## 2959 0.05979228 209 0
## 2964 0.47515526 209 0
## 2971 0.04786629 209 0roads_tmp <- SpatialLinesDataFrame(roads_tmp,
data = tmp,
match.ID = FALSE)
par(mfrow = c(1, 3))
plot(roads_tmp)
road_class <- unique(roads_tmp$AV_LEGEND)
shades <- rev(brewer.pal(length(road_class), "Spectral"))
tmp <- roads_tmp$AV_LEGEND
index <- match(tmp, as.vector(road_class))
plot(roads_tmp, col = shades[index], lwd = 3)
plot(roads_tmp, lwd = roads_tmp$LENGTH_MI * 10)
par(mfrow = c(1, 1))